Add task category and link to CDM paper (#2)

- Add task category and link to CDM paper (6877d4fcfac51b885b2f1c3e94ea3ab8686e0dfc)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,16 +1,19 @@
 ---
-license: apache-2.0
 language:
 - en
 - zh
+license: apache-2.0
+size_categories:
+- 1M<n<10M
 pretty_name: UniMER_Dataset
 tags:
 - data
 - math
 - MER
-size_categories:
-- 1M<n<10M
+task_categories:
+- image-to-text
 ---
+
 # UniMER Dataset
 
 For detailed instructions on using the dataset, please refer to the project homepage: [UniMERNet Homepage](https://github.com/opendatalab/UniMERNet/tree/main)
@@ -31,7 +34,6 @@ The UniMER dataset is a specialized collection curated to advance the field of M
     - Handwritten Expressions (HWE): 6,332 samples
   - Purpose: To provide a thorough evaluation of MER models across a spectrum of real-world conditions
 
-
 ## Visual Data Samples
 ![UniMER-Test](https://github.com/opendatalab/UniMERNet/assets/69186975/7301df68-e14c-4607-81bc-b6ee3ba1780b)
   
@@ -51,8 +53,9 @@ The UniMER dataset is a specialized collection curated to advance the field of M
 ‡ For copyright compliance, please manually download this dataset portion: [HME100K dataset](https://ai.100tal.com/dataset).
 
 ## Acknowledgements
-We would like to express our gratitude to the creators of the [Pix2tex](https://github.com/lukas-blecher/LaTeX-OCR), [CROHME](https://www.cs.rit.edu/~rlaz/files/CROHME+TFD%E2%80%932019.pdf), and [HME100K](https://github.com/tal-tech/SAN) datasets. Their foundational work has significantly contributed to the development of the UniMER dataset. 
+We would like to express our gratitude to the creators of the [Pix2tex](https://github.com/lukas-blecher/LaTeX-OCR), [CROHME](https://www.cs.rit.edu/~rlaz/files/CROHME+TFD%E2%80%932019.pdf), and [HME100K](https://github.com/tal-tech/SAN) datasets. Their foundational work has significantly contributed to the development of the UniMER dataset.
 
+A new metric for evaluating this dataset is presented in [CDM: A Reliable Metric for Fair and Accurate Formula Recognition Evaluation](https://huggingface.co/papers/2409.03643).
 
 ## Citations
 
@@ -129,9 +132,9 @@ UniMER数据集是专门为通用数学表达式识别（MER）发布的数据
 }
 
 @misc{conghui2022opendatalab,
-    author={He, Conghui and Li, Wei and Jin, Zhenjiang and Wang, Bin and Xu, Chao and Lin, Dahua},
+    author={He, Conghui and Li, Wei, Jin, Zhenjiang and Wang, Bin and Xu, Chao and Lin, Dahua},
     title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets},
     howpublished = {\url{https://opendatalab.com}},
     year={2022}
 }
-```
+```